SU‐G‐TeP3‐12: Retrospective Assessment of R2star Using Ultra‐High Field MRI in a Rodent Model of Radiation Necrosis
Bibliographic record
Abstract
Purpose: To establish a quantitative MRI method that would be capable of predicting radiation necrosis without using a contrast agent. Methods: Healthy male Fischer 344 rats were irradiated using an animal irradiator capable of delivering 2.3 Gy/min with a kVp of 225 V. A dose of 40 Gy was given to half the brain in a single session. Rats were scanned using a 9.4 T animal MRI before irradiation and every two weeks following radiation until either necrosis developed or they were sacrificed for health reasons. A multi‐echo gradient‐echo sequence was acquired at every time point and the apparent transverse relaxation rate R 2 * was calculated based on the measured signal decay. At the last time point, an ROI mask with an R 2 * value of greater than 45 s −1 was applied in the area of the external and internal capsule where radiation necrosis was confirmed. A retrospective analysis was performed to determine whether R 2 * values would be able to predict where radiation necrosis would occur. Results: Radiation necrosis was morphologically visible between weeks 22–24 following treatment. Gadolinium MRI and histology confirmed radiation necrosis in the area of MRI enhancement. Our data suggests that there is a trend towards significance in the lesion as early as 12 weeks prior to morphological changes on MRI with significance occurring 6 weeks prior (p≤0.05, p≤0.01 at week 24). Measurements of the R 2 * in the hippocampus did not show any significant difference; however, there are areas of visible R 2 * change within sub‐hippocampal regions. Conclusion: R 2 * is a promising method that could be able to predict an underlying disease process that occurs prior to radiation necrosis. The constant increase in R 2 * values suggests a possible neuroinflammatory mechanism rather than an acute vascular event where R 2 * would tend to decrease in the area.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".